MétaCan
Menu
Back to cohort

Medulloblastoma: From Molecular Subgroups to Molecular Targeted Therapies

2018· review· en· W2796721182 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Neuroscience · 2018
Typereview
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHospital for Sick Children
FundersNational Institute of Neurological Disorders and StrokeNational Cancer Institute
KeywordsMedulloblastomaDiseaseTargeted therapyMedicineCarcinogenesisRadiation therapyBioinformaticsOncologyCancerBiologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

Brain tumors are the leading cause of cancer-related death in children, and medulloblastoma (MB) is the most common malignant pediatric brain tumor. Advances in surgery, radiation, and chemotherapy have improved the survival of MB patients. But despite these advances, 25-30% of patients still die from the disease, and survivors suffer severe long-term side effects from the aggressive therapies they receive. Although MB is often considered a single disease, molecular profiling has revealed a significant degree of heterogeneity, and there is a growing consensus that MB consists of multiple subgroups with distinct driver mutations, cells of origin, and prognosis. Here, we review recent progress in MB research, with a focus on the genes and pathways that drive tumorigenesis, the animal models that have been developed to study tumor biology, and the advances in conventional and targeted therapy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.346
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it